关于动态测量误差修正方法的对比分析
Comparison and Analysis of Dynamic Measurement Error Correction Methods
毛廷鎏 1赵建印 1耿东 1吴一乔 1雷瑶1
作者信息
摘要
在产品测试过程中,由于测试设备自身误差和测试人员专业素质等因素,导致测量值与实际值相比,会存在一定的偏差.当前,解决这一问题的普遍做法是将测量误差通过一定的算法手段进行去除.针对当前误差修正方法普遍不适用于动态测量误差修正的缺点,论文研究了基于贝叶斯、灰色模型及卡尔曼滤波的动态误差修正方法,并对这几种方法进行了应用对比,为选择合理的误差修正模型提供思路,解决测量数据的误差问题.
Abstract
In the process of product testing,due to the error of the testing equipment itself and the professional quality of the tester and other factors,there will be a certain deviation between the measured value and the actual value.At present,the common way to solve this problem is to remove the measurement error by certain algorithm means.In view of the shortcomings that the current error correction methods are generally not suitable for the dynamic measurement error correction,this paper studies the dynamic er-ror correction methods based on Bayesian,Grey model and Kalman filter,and compares the application of these methods,so as to provide ideas for selecting a reasonable error correction model and solving the error problem of measurement data.
关键词
误差修正/贝叶斯/灰色模型/卡尔曼滤波Key words
error correction/Bayesian/grey model/Kalman filter引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据